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2016 3rd International Conference on Materials Engineering,Manufacturing technology and Control(ICMEMTC 2016)

作者： Jie Chen Degan Zhang School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education

In embedded Internet of Things(IOT) environment, there are the troubles such as complex background, illumination changes, shadows and other factors for detecting moving object, so we put forward a new detection service method through mixing Gaussian Mixture Model(GMM), edge detection service method and continuous frame difference method in this paper. In time domain, the new method uses GMM to model and updates the background. In spatial domain, it uses the hybrid detection service method which mixes edge detection service method, continuous frame difference method and GMM to get initial contour of moving object, and gets ultimate moving object. This method not only can well adapt to the illumination gradients and background disturbance occurred on scene, but also can well solve some problems such as inaccurate target detection, incomplete edge detection, cavitation and ghost which usually appears in traditional method. As experimental result showing, this method holds better real-time and robustness. It is not only easily implemented, but also can accurately detect moving object.

关键词： GMM embedded IOT moving object detection service

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Macro liveness graph and liveness of ω-independent unbounded nets

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Science China(Information Sciences) 2015年第3期58卷 132-141页

作者： WANG ShouGuang GAN MengDi ZHOU MengChu School of Information and Electronic Engineering Zhejiang Gongshang University Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

Liveness is a basic property of a system and the liveness issue of unbounded Petri nets remains one of the most difficult problems in this *** work proposes a novel method to decide the liveness of a class of unbounded generalized Petri nets calledω-independent unbounded nets,breaking the existing limits to one-place-unbounded *** algorithm to construct a macro liveness graph(MLG)is developed and a critical condition based on MLG deciding the liveness ofω-independent unbounded nets is *** are provided to demonstrate its effectiveness.

关键词： discrete event system(DES) Petri nets complex systems liveness property analysis

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A New ETL Approach Based on Data Virtualization

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Journal of computer Science & technology 2015年第2期30卷 311-323页

作者：郭树盛袁子牧孙傲冰岳强 State Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China

ETL （Extract-Transform-Load） usually includes three phases： extraction, transformation, and loading. In building data warehouse, it plays the role of data injection and is the most time-consuming activity. Thus it is necessary to improve the performance of ETL. In this paper, a new ETL approach, TEL （Transform-Extract-Load） is proposed. The TEL approach applies virtual tables to realize the transformation stage before extraction stage and loading stage, without data staging area or staging database which stores raw data extracted from each of the disparate source data systems. The TEL approach reduces the data transmission load, and improves the performance of query from access layers. Experimental results based on our proposed benchmarks show that the TEL approach is feasible and practical.

关键词： cloud computing big data ETL heterogeneous database data virtualization

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A Reduced Reachability Tree for a Class of Unbounded Petri Nets

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IEEE/CAA Journal of Automatica Sinica 2015年第4期2卷 345-352页

作者： Shouguang Wang Mengdi Gan Mengchu Zhou Dan You School of Information and Electronic Engineering Zhejiang Gongshang University State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Ministry of Education(MoE)Key Laboratory of Embedded System and Service Computing Tongji University MoE Key Laboratory of Embedded System and Service Computing Tongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

As a powerful analysis tool of Petri nets, reachability trees are fundamental for systematically investigating many characteristics such as boundedness, liveness and reversibility. This work proposes a method to generate a reachability tree, called ωRT for short, for a class of unbounded generalized nets called ω-independent nets based on new modified reachability trees (NMRTs). ωRT can effectively decrease the number of nodes by removing duplicate and ω-duplicate nodes in the tree, and verify properties such as reachability, liveness and deadlocks. Two examples are provided to show its superiority over NMRTs in terms of tree size. © 2014 Chinese Association of Automation.

关键词： Petri nets

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F-CNN: An FPGA-based framework for training Convolutional Neural Networks

F-CNN: An FPGA-based framework for training Convolutional Ne...

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International Conference on Application Specific systems (ASAP), Architectures and Processors

作者： Wenlai Zhao Haohuan Fu Wayne Luk Teng Yu Shaojun Wang Bo Feng Yuchun Ma Guangwen Yang Ministry of Education Key Laboratory for Earth System Modeling and Center for Earth System Science Tsinghua University China Tsinghua National Laboratory for Information Science and Technology China Department of Computing Imperial college London UK Department of Automatic Test and Control Harbin Institute of Technology China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781509015047

This paper presents a novel reconfigurable framework for training Convolutional Neural Networks (CNNs). The proposed framework is based on reconfiguring a streaming datapath at runtime to cover the training cycle for the various layers in a CNN. The streaming datapath can support various parameterized modules which can be customized to produce implementations with different trade-offs in performance and resource usage. The modules follow the same input and output data layout, simplifying configuration scheduling. For different layers, instances of the modules contain different computation kernels in parallel, which can be customized with different layer configurations and data precision. The associated models on performance, resource and bandwidth can be used in deriving parameters for the datapath to guide the analysis of design trade-offs to meet application requirements or platform constraints. They enable estimation of the implementation specifications given different layer configurations, to maximize performance under the constraints on bandwidth and hardware resources. Experimental results indicate that the proposed module design targeting Maxeler technology can achieve a performance of 62.06 GFLOPS for 32-bit floating-point arithmetic, outperforming existing accelerators. Further evaluation based on training LeNet-5 shows that the proposed framework achieves about 4 times faster than CPU implementation of Caffe and about 7.5 times more energy efficient than the GPU implementation of Caffe.

关键词： Training Field programmable gate arrays Convolution Computational modeling Bandwidth Neural networks Runtime

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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits (vol 50, pg 1412, 2018)

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NATURE GENETICS 2018年第12期50卷 1755-1755页

作者： Evangelou, Evangelos Warren, Helen R. Mosen-Ansorena, David Mifsud, Borbala Pazoki, Raha Gao, He Ntritsos, Georgios Dimou, Niki Cabrera, Claudia P. Karaman, Ibrahim Fu Liang Ng Evangelou, Marina Witkowska, Katarzyna Tzanis, Evan Hellwege, Jacklyn N. Giri, Ayush Edwards, Digna R. Velez Sun, Yan V. Cho, Kelly Gaziano, J. Michael Wilson, Peter W. F. Tsao, Philip S. Kovesdy, Csaba P. Esko, Tonu Magi, Reedik Milani, Lili Almgren, Peter Boutin, Thibaud Debette, Stephanie Ding, Jun Giulianini, Franco Holliday, Elizabeth G. Jackson, Anne U. Li-Gao, Ruifang Lin, Wei-Yu Luan, Jian'an Mangino, Massimo Oldmeadow, Christopher Prins, Bram Peter Qian, Yong Sargurupremraj, Muralidharan Shah, Nabi Surendran, Praveen Theriault, Sebastien Verweij, Niek Willems, Sara M. Zhao, Jing-Hua Amouyel, Philippe Connell, John de Mutsert, Renee Doney, Alex S. F. Farrall, Martin Menni, Cristina Morris, Andrew D. Noordam, Raymond Pare, Guillaume Poulter, Neil R. Shields, Denis C. Stanton, Alice Thom, Simon Abecasis, Goncalo Amin, Najaf Arking, Dan E. Ayers, Kristin L. Barbieri, Caterina M. Batini, Chiara Bis, Joshua C. Blake, Tineka Bochud, Murielle Boehnke, Michael Boerwinkle, Eric Boomsma, Dorret I. Bottinger, Erwin P. Braund, Peter S. Brumat, Marco Campbell, Archie Campbell, Harry Chakravarti, Aravinda Chambers, John C. Chauhan, Ganesh Ciullo, Marina Cocca, Massimiliano Collins, Francis Cordell, Heather J. Davies, Gail de Borst, Martin H. de Geus, Eco J. Deary, Ian J. Deelen, Joris Del Greco, Fabiola M. Demirkale, Cumhur Yusuf Dorr, Marcus Ehret, Georg B. Elosua, Roberto Enroth, Stefan Erzurumluoglu, A. Mesut Ferreira, Teresa Franberg, Mattias Franco, Oscar H. Gandin, Ilaria Gasparini, Paolo Giedraitis, Vilmantas Gieger, Christian Girotto, Giorgia Goel, Anuj Gow, Alan J. Gudnason, Vilmundur Guo, Xiuqing Gyllensten, Ulf Hamsten, Anders Harris, Tamara B. Harris, Sarah E. Hartman, Catharina A. Havulinna, Aki S. Hicks, Andrew A. Hofer, Edith Hofman, Albert Hottenga, Jouke-Jan Huffman, Jennifer E. Hwang, Shih-Jen Ingelsson, Erik James, Alan Jansen Department of Epidemiology and Biostatistics Imperial College London London UK Department of Hygiene and Epidemiology University of Ioannina Medical School Ioannina Greece William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK National Institute for Health Research Barts Cardiovascular Biomedical Research Center Queen Mary University of London London UK MRC-PHE Centre for Environment and Health Imperial College London London UK Department of Mathematics Imperial College London London UK Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Medical Center Tennessee Valley Healthcare System (626)/Vanderbilt University Nashville TN USA Vanderbilt Genetics Institute Vanderbilt Epidemiology Center Department of Obstetrics and Gynecology Vanderbilt University Medical Center Tennessee Valley Health Systems VA Nashville TN USA Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA Department of Biomedical Informatics Emory University School of Medicine Atlanta GA USA Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA Division of Aging Department of Medicine Brigham and Women’s Hospital Department of Medicine Harvard Medical School Boston MA USA Atlanta VAMC and Emory Clinical Cardiovascular Research Institute Atlanta GA USA VA Palo Alto Health Care System Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA Nephrology Section Memphis VA Medical Center and University of Tennessee Health Science Center Memphis TN USA Estonian Genome Center University of Tartu Tartu Estonia Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Department Clinical Sciences Malmö Lund University Malmö Sweden MRC Human Genetics Un

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

关键词： Cardiovascular diseases Genome informatics Genome-wide association studies

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Optimizing Parallel Kinetic Monte Carlo Simulation by Communication Aggregation and Scheduling

Optimizing Parallel Kinetic Monte Carlo Simulation by Commun...

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2015大数据技术及应用论坛

作者： Baodong Wu Shigang Li Yunquan Zhang State Key Laboratory of Computer System and Architecture Institute of Computing TechnologyChinese Academy of Sciences

Kinetic Monte Carlo(KMC) algorithm has been widely applied for simulation of radiation damage, grain growth and chemical reactions. To simulate at a large temporal and spatial scale, domain decomposition is commonly used to parallelize the KMC algorithm. However, through experimental analysis, we find that the communication overhead is the main bottleneck which affects the overall performance and limits the scalability of parallel KMC algorithm on large-scale clusters. To alleviate the above problems, we present a communication aggrega‐tion approach to reduce the total number of messages and eliminate the commu‐nication redundancy, and further utilize neighborhood collective operations to optimize the communication scheduling. Experimental results show that the opti‐mized KMC algorithm exhibits better performance and scalability compared with the well-known open-source library—SPPARKS. On 32-node Xeon E5-2680 cluster(total 640 cores), the optimized algorithm reduces the total execution time by 16 %, reduces the communication time by 50 % on average, and achieves 24 times speedup over the single node(20 cores) execution.

关键词： Domain decomposition Communication aggregation Communication scheduling Neighborhood collectives

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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems

Advances in Modelling and Analysis A

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Advances in Modelling and Analysis A 2016年第1期53卷 145-159页

作者： Wu, Daqing Tang, Lixiang Li, Haiyan Ouyang, LiJun Computer Science and Technology Institute University of South China HangyangHunan China Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200240 China Zigong643000 China Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence Guangxi University for Nationalities Nanning530006 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HefeiAnhui Province230039 China Department of Business Administration Hunan University of Finance and Economics Hunan410205 China

This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through comparisons with other two multi-objective algorithms using established benchmarks and metrics. Simulation results demonstrated that DTPSO shows competitive, if not better, performance as compared to the other algorithms. © 2016, AMSE Press. All rights reserved.

关键词： Multiobjective optimization

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A polynomial algorithm to performance analysis of concurrent systems via petri nets and ordinary differential equations

A polynomial algorithm to performance analysis of concurrent...

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作者： Ding, Zuohua Zhou, Yuan Zhou, Meng Chu Laboratory of Intelligent Computing and Software Engineering Zhejiang Sci-Tech University Hangzhou310018 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102-1982 United States

In this paper, a new method is proposed to evaluate the performance of concurrent systems. A concurrent system consisting of multiple processes that communicate via message passing mechanisms is modeled by a Petri net, which is in turn represented by a set of ordinary differential equations (ODEs) of a restricted type. The equations describe the system state changes, and the solutions, also called state measures, can be used for the performance analysis such as estimating response time, throughput and efficiency. This method can avoid a state explosion problem encountered by the conventional methods based on Continuous-Time Markov Chains. Its application to an IBM business system is given as an example. © 2004-2012 IEEE.

关键词： Ordinary differential equations

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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